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Record W1966751274 · doi:10.4236/health.2012.412a226

Obesity-associated steatotic liver exhibits aberrant or altered sphingolipid composition and preferentially accumulates ceramide species containing long chain fatty acids

2012· article· en· W1966751274 on OpenAlexaff
Erin Lynn Burrows, Ranjana P. Bird

Bibliographic record

VenueHealth · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSphingolipid Metabolism and Signaling
Canadian institutionsUniversity of WindsorUniversity of Waterloo
Fundersnot available
KeywordsSphingolipidCeramideSphingomyelinLipidomicsSphingosineLipid signalingSteatosisSphingosine-1-phosphateDownregulation and upregulationBiochemistryFatty liverInternal medicineBiologyChemistryEndocrinologyEnzymeCholesterolApoptosisMedicineReceptor

Abstract

fetched live from OpenAlex

The sphingolipid (SL) signaling pathways are induced by reactive oxygen species and proin-flammatory molecules, which are shown to be upregulated in the obese state. The present work was conducted to determine if an altered SL pathway exists, and contributes to the pathogenesis of hepatic steatosis associated with obesity. Steatotic and non-steatotic livers were procured from Zucker Obese female rats and their lean counterparts in this pre-clinical study, and assessed for enzymes involved in degradation as well as in phos-phorylation of proapoptotic SLs. The expression of enzymes [sphingo-myelinase (SMase), ceramidase, and sphingosine kinase-1 (SK1)] and apoptotic proteins (Bax and Bcl-2) was quantified by ELISA and by Western Blot. Sphingomyelin (SM), ceramide, ceramide-1 phosphate (C1P), sphingosine (SPH), and sphingosine-1-phosphate (S1P) levels were quantified by high-performance liquid chroma-tography (HPLC)-tandem mass spectroscopy (MS). Obese steatotic livers exhibited significantly upregulated ceramidase and down-regulated SK1 and C1P levels (P accumulation of ceramides containing long chain fatty acids could be involved in the pathogenesis of hepatic steatosis.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.554
Threshold uncertainty score0.925

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.042
GPT teacher head0.286
Teacher spread0.244 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2012
Admission routes1
Has abstractyes

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